Labira/indobert-qa-articles

This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 3.1139
• Validation Loss: 4.3506
• Epoch: 11

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 64, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
5.7935	5.4861	0
5.0514	5.1407	1
4.3851	4.7235	2
3.9141	4.5696	3
3.6585	4.4246	4
3.3704	4.3449	5
3.2069	4.3397	6
3.0818	4.3506	7
3.0552	4.3506	8
3.0760	4.3506	9
3.1019	4.3506	10
3.1139	4.3506	11

Framework versions

• Transformers 4.40.0
• TensorFlow 2.15.0
• Datasets 2.19.0
• Tokenizers 0.19.1